btmodel | R Documentation |
btmodel
is a basic fitting function for simple Bradley-Terry models.
btmodel(y, weights = NULL, type = c("loglin", "logit"), ref = NULL,
undecided = NULL, position = NULL, start = NULL, vcov = TRUE, estfun =
FALSE, ...)
y |
paircomp object with the response. |
weights |
an optional vector of weights (interpreted as case weights). |
type |
character. Should an auxiliary log-linear Poisson model or logistic binomial be employed for estimation? The latter is not available if undecided effects are estimated. |
ref |
character or numeric. Which object parameter should be the reference category, i.e., constrained to zero? |
undecided |
logical. Should an undecided parameter be estimated? |
position |
logical. Should a position effect be estimated? |
start |
numeric. Starting values when calling |
vcov |
logical. Should the estimated variance-covariance be included in the fitted model object? |
estfun |
logical. Should the empirical estimating functions (score/gradient contributions) be included in the fitted model object? |
... |
further arguments passed to functions. |
btmodel
provides a basic fitting function for Bradley-Terry models,
intended as a building block for fitting Bradley-Terry trees and
Bradley-Terry mixtures in the psychotree package, respectively. While
btmodel
is intended for individual paired-comparison data, the
eba package provides functions for aggregate data.
btmodel
returns an object of class "btmodel"
for which
several basic methods are available, including print
, plot
,
summary
, coef
, vcov
, logLik
, estfun
and worth
.
btmodel
returns an S3 object of class "btmodel"
,
i.e., a list with components as follows.
y |
paircomp object with the response |
coefficients |
estimated parameters on log-scale (without the first parameter which is always constrained to be 0), |
vcov |
covariance matrix of the parameters in the model, |
loglik |
log-likelihood of the fitted model, |
df |
number of estimated parameters, |
weights |
the weights used (if any), |
n |
number of observations (with non-zero weights), |
type |
character for model type (see above), |
ref |
character for reference category (see above), |
undecided |
logical for estimation of undecided parameter (see above), |
position |
logical for estimation of position effect (see above), |
labels |
character labels of the objects compared, |
estfun |
empirical estimating function (also known as scores or gradient contributions). |
pcmodel
, gpcmodel
, rsmodel
,
raschmodel
, nplmodel
, the eba package
o <- options(digits = 4)
## data
data("GermanParties2009", package = "psychotools")
## Bradley-Terry model
bt <- btmodel(GermanParties2009$preference)
summary(bt)
plot(bt)
options(digits = o$digits)
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